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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

NIBIO's Scientific Publications →

2025

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Authors

Zahra Bitarafan Melissa Magerøy Rafael de Andrade Moral Najmeh Salehan Kristian Schmidt Nielsen Christian Andreasen

Abstract

No abstract has been registered

Authors

Anne Muola Belachew Asalf Tadesse

Abstract

No abstract has been registered

Authors

Stian Folvik May Bente Brurberg Anupam Gogoi

Abstract

No abstract has been registered

Authors

Melissa Magerøy Paal Krokene Marcos Viejo

Abstract

No abstract has been registered

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Authors

Joyce Machado Nunes Romeiro Victor Strimbu Tron Haakon Eid Annika Kangas

Abstract

No abstract has been registered

Authors

Payel Bhattacharjee Mari Talgø Syvertsen Igor A. Yakovlev Marcos Viejo Somoano Torgeir Rhoden Hvidsten Mallikarjuna Rao Kovi Jorunn Elisabeth Olsen Carl Gunnar Fossdal

Abstract

No abstract has been registered

Authors

Payel Bhattacharjee Mari Talgø Syvertsen Igor A. Yakovlev Marcos Viejo Somoano Torgeir Rhoden Hvidsten Jorunn Elisabeth Olsen Carl Gunnar Fossdal

Abstract

No abstract has been registered

Authors

Oda Eline Sandmo Ånesland Tage Thorstensen May Bente Brurberg

Abstract

No abstract has been registered

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Authors

Frank Thomas Ndjomatchoua Richard Olaf James Hamilton Stutt Ritter Atoundem Guimapi Luca Rossini Christopher A Gilligan

Abstract

No abstract has been registered

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Authors

Frank Thomas Ndjomatchoua Richard Olaf James Hamilton Stutt Ritter Atoundem Guimapi Luca Rossini Christopher A. Gilligan

Abstract

Empirical field data and simulation models are often used separately to monitor and analyse the dynamics of insect pest populations over time. Greater insight may be achieved when field data are used directly to parametrize population dynamic models. In this paper, we use a differential evolution algorithm to integrate mechanistic physiological-based population models and monitoring data to estimate the population density and the physiological age of the first cohort at the start of the field monitoring. We introduce an ad hoc temperature-driven life-cycle model of Bemisia tabaci in conjunction with field monitoring data. The likely date of local whitefly invasion is estimated, with a subsequent improvement of the model’s predictive accuracy. The method allows computation of the likely date of the first field incursion by the pest and demonstrates that the initial physiological age somewhat neglected in prior studies can improve the accuracy of model simulations. Given the increasing availability of monitoring data and models describing terrestrial arthropods, the integration of monitoring data and simulation models to improve model prediction and pioneer invasion date estimate will lead to better decision-making in pest management.